I have a project with an existing database which was initially created for a legacy application. It works fine, but over time quite a few of the tables / fields have been lost or under-utilized, but the historical data MAY be useful someday so they're not going anywhere.
Enter 2012 ('13) and Entity Framework 5, an ORM with built in POCO generation (Nice Add!). So bang.. Get a connection to the Oracle Database, gen. up a context and some POCO's.. suh-weet!! But wait.. my POCO's arent really the POCO's I would like to deal with... There's a bunch of fields which i dont need anymore (not to say I'll NEVER need them, but i can't know for sure), so now i've got these POCO's which are basically bloated table mappers... So what should I do.
I see a few solutions here..
1). I could throw them around and only use the fields that I need.
2). I could get into the Model Surface and start axing the unused fields.
3). "Code-First" approach and tie the objects into the existing DB, it's a large DB though (i'm pretty sure this is possible, right?)
4). Create my own POCO / DTO's in it's own model project and these will essentially become my "domain model", but the mapping back into the context could be painful..
Lastly, do these POCO's / DTO's need to be in their own project?? What is there REALLY to gain.. seeing things like "YAGNI", i feel like it can sit right under the .edmx and never bother anyone..
On a side note, i will be needing a few of these via JSON too, so the whole serializable ability needs to be considered..
Can i just partial class the generated POCO's and only "Attribute" the properties I'll be needing?
anyhow, it'd be great to hear from past experience, or thoughts on the matter..
I could see this being in Programmers, but i figured I'd start it here.
We have a very similar situation, a large legacy DB2 database of which we need small portions of specific tables for our applications.
To do this we used entity framework code first models for the relevant subsections of data we were interested in. This meant we could do a few important things:
remove irrelevant data from the model to make code more discoverable
rename fields inside our model and map them to names that make sense in the app rather than existing column names
reduce the volume of data pulled back by queries (ie our selects dont grab all the extra bits)
where 2 formats of data exist use the modern standard rather than historical format
This works out really well for us, however a couple of things to note:
if you are writing make sure you include all required fields in the model
you can generate you CF classes but you will have to trim them a bit
generating from non mssql can sometimes be more tricky
In terms of json serialisation we do this too however we use a different model for this and use automapper to translate. You should in most cases be able to serialise without needing to add extra attributes but if they are required you can just add them to your pocos alongside any ef attributes.
I'm researching data layer underpinnings for a new web-based reporting system and have spent a lot of time evaluating ORM's over the last few days. That said, I've never dealt with "lazy loading" before and am confused at why its the default setting for LINQ queries in the Entity Framework. It seems like it creates a lot of network traffic and unnecessarily tasks the database with additional queries that could otherwise be resolved with joins.
Can someone describe a scenario in which lazy loading would be beneficial?
Some meta:
The new system will be working against a database with hundreds of tables and many terabytes of data in a production environment with over 3,000 concurrent users on the system 24 hours a day. They will be retrieving large datasets continuously. Is it possible that an ORM just isn't the right solution for our needs, especially since the app will be web-based?
When we talk about lazy loading we are talking about Navigation Properties (how we follow foreign keys). What lazy loading will do for us is to populate the entity from a remote table as we attempt to access that entity. For example if we have a model like this
public class TestEntity
{
public int Id{get;set;}
public AnotherEntity RemoteEntity{get;set;}
}
And call the following
var something = WhateverContext.TestEntities.First().RemoteEntity;
We will get 2 database calls, one for WhateverContext.TestEntities.First() and one for loading the remote entity.
I'm a web guy, (and more specifically an MVC guy) and for web stuff I don't think there is ever a good reason for wanting to do this, One database call is always going to be quicker than two if we require the same set of data.
The situation where I think that lazy loading is actually worth considering is when you don't know when you do your first query if you will need the second entity at all. In my opinion this is much more relevant for windows applications where we have a user who is performing actions in real time (rather than stateless MVC where users are requesting whole pages at once). For example I think lazy loading shines when we have a list of data with a details link, then we don't load the details until the user decides they want to see them.
I don't feel this extends to paging, sorting and filtering, IMO there should be one specifically crafted database query per page of data you are displaying, which returns exactly the data set required to display that page.
In terms of your performance question, I feel that EF (or another ORM) can probably meet your needs here but you want to be careful with how you are retrieving large datasets due to the way EF tracks entities. Check out my EF performance tuning cheat sheet, and read up on DetectChanges and AsNoTracking if you do decide to use EF with large queries.
Most ORMs will give you the option, when you're building up your object selections, to say "don't be lazy, go ahead and join", so if you're worried about it from an efficiency perspective, don't be. You can make it work (usually).
There are 2 particular cases I know of where lazy loading helps:
Chaining commands
What if you want to create a basic select, but then you want to run it through a sort and a filter function that's based on user input. You can simply pass the ORM object in, and attach the sort and filtering functionality to it. Instead of evaluating it each time, it only evaluates when it's actually used.
Avoiding huge, deep, highly-relational queries
What if you just need the IDs of some related fields? If it loads lazily, you don't have to worry about it joining a whole bunch of data and tables that you don't need, potentially slowing down the query and overusing bandwidth. Of course, if you DID want everything else, then you'll need to be explicit, or you may run into a problem where it lazily runs a query for each detail record. Like I mentioned at the outset, that's easily overcome in any ORM worth using.
A simple case is a result set of N records which you do not want to bring to the client at once. The benefit is that you are able to lazily load only what is needed for the clients demands, such as sorting, filtering, etc... An example would be a paging view where one could page through records and sort them accordingly, thus the client only needs N amount at a given time.
When you perform the LINQ query it translates that to SQL commands on the server side to provide only what is needed in the given context. It boils down to offloading work to the database and minimizing what you need to send back to the client.
Some will argue that ORM based lazy loading is wrong however that starts to move to semantics fairly quick and should be more about approach to design versus what is right and wrong.
I've developed on the Yii Framework for a while now (4 months), and so far I have encountered some issues with MVC that I want to share with experienced developers out there. I'll present these issues by listing their levels of complexity.
[Level 1] CR(create update) form. First off, we have a lot of forms. Each form itself is a model, so each has some validation rules, some attributes, and some operations to perform on the attributes. In a lot of cases, each of these forms does both updating and creating records in the db using a single active record object.
-> So at this level of complexity, a form has to
when opened,
be able to display the db-friendly data from the db in a human-friendly way
be able to display all the form fields with the attributes of the active record object. Adding, removing, altering columns from the db table has to affect the display of the form.
when saves, be able to format the human-friendly data to db-friendly data before getting the data
when validates, be able to perform basic validations enforced by the active record object, it also has to perform other validations to fulfill some business rules.
when validating fails, be able to roll back changes made to the attribute as well as changes made to the db, and present the user with their originally entered data.
[Level 2] Extended CR form. A form that can perform creation/update of records from different tables at once. Not just that, whether a form would create/update of one of its records can sometimes depend on other conditions (more business rules), so a form can sometimes update records at table A,B but not D, and sometimes update records at A,D but not B
-> So at this level of complexity, we see a form has to:
be able to satisfy [Level 1]
be able to conditionally create/update of certain records, conditionally create/update of certain columns of certain records.
[Level 3] The Tree of Models. The role of a form in an application is, in many ways, a port that let user's interact with your application. To satisfy requests, this port will interact with many other objects which, in turn, interact with many more objects. Some of these objects can be seen as models. Active Record is a model, but a Mailer can also be a model, so is a RobotArm. These models use one another to satisfy a user's request. Each model can perform their own operation and the whole tree has to be able to roll back any changes made in the case of error/failure.
Has anyone out there come across or been able to solve these problems?
I've come up with many stuffs like encapsulating model attributes in ModelAttribute objects to tackle their existence throughout tiers of client, server, and db.
I've also thought we should give the tree of models an Observer to observe and notify the observed models to rollback changes when errors occur. But what if multiple observers can exist, what if a node use its parent's observer but give its children another observers.
Engineers, developers, Rails, Yii, Zend, ASP, JavaEE, any MVC guys, please join this discussion for the sake of science.
--Update to teresko's response:---
#teresko I actually intended to incorporate the services into the execution inside a unit of work and have the Unit of work not worry about new/updated/deleted. Each object inside the unit of work will be responsible for its state and be required to implement their own commit() and rollback(). Once an error occur, the unit of work will rollback all changes from the newest registered object to the oldest registered object, since we're not only dealing with database, we can have mailers, publishers, etc. If otherwise, the tree executes successfully, we call commit() from the oldest registered object to the newest registered object. This way the mailer can save the mail and send it on commit.
Using data mapper is a great idea, but We still have to make sure columns in the db matches data mapper and domain object. Moreover, an extended CR form or a model that has its attributes depending on other models has to match their attributes in terms of validation and datatype. So maybe an attribute can be an object and shipped from model to model? An attribute can also tell if it's been modified, what validation should be performed on it, and how it can be human-friendly, application-friendly, and db-friendly. Any update to the db schema will affect this attribute, and, thereby throwing exceptions that requires developers to make changes to the system to satisfy this change.
The cause
The root of your problem is misuse of active record pattern. AR is meant for simple domain entities with only basic CRUD operations. When you start adding large amount of validation logic and relations between multiple tables, the pattern starts to break apart.
Active record, at its best, is a minor SRP violation, for the sake of simplicity. When you start piling on responsibilities, you start to incur severe penalties.
Solution(s)
Level 1:
The best option is the separate the business and storage logic. Most often it is done by using domain object and data mappers:
Domain objects (in other materials also known as business object or domain model objects) deal with validation and specific business rules and are completely unaware of, how (or even "if") data in them was stored and retrieved. They also let you have object that are not directly bound to a storage structures (like DB tables).
For example: you might have a LiveReport domain object, which represents current sales data. But it might have no specific table in DB. Instead it can be serviced by several mappers, that pool data from Memcache, SQL database and some external SOAP. And the LiveReport instance's logic is completely unrelated to storage.
Data mappers know where to put the information from domain objects, but they do not any validation or data integrity checks. Thought they can be able to handle exceptions that cone from low level storage abstractions, like violation of UNIQUE constraint.
Data mappers can also perform transaction, but, if a single transaction needs to be performed for multiple domain object, you should be looking to add Unit of Work (more about it lower).
In more advanced/complicated cases data mappers can interact and utilize DAOs and query builders. But this more for situation, when you aim to create an ORM-like functionality.
Each domain object can have multiple mappers, but each mapper should work only with specific class of domain objects (or a subclass of one, if your code adheres to LSP). You also should recognize that domain object and a collection of domain object are two separate things and should have separate mappers.
Also, each domain object can contain other domain objects, just like each data mapper can contain other mappers. But in case of mappers it is much more a matter of preference (I dislike it vehemently).
Another improvement, that could alleviate your current mess, would be to prevent application logic from leaking in the presentation layer (most often - controller). Instead you would largely benefit from using services, that contain the interaction between mappers and domain objects, thus creating a public-ish API for your model layer.
Basically, services you encapsulate complete segments of your model, that can (in real world - with minor effort and adjustments) be reused in different applications. For example: Recognition, Mailer or DocumentLibrary would all services.
Also, I think I should not, that not all services have to contain domain object and mappers. A quite good example would be the previously mentioned Mailer, which could be used either directly by controller, or (what's more likely) by another service.
Level 2:
If you stop using the active record pattern, this become quite simple problem: you need to make sure, that you save only data from those domain objects, which have actually changed since last save.
As I see it, there are two way to approach this:
Quick'n'Dirty
If something changed, just update it all ...
The way, that I prefer is to introduce a checksum variable in the domain object, which holds a hash from all the domain object's variables (of course, with the exception of checksum it self).
Each time the mapper is asked to save a domain object, it calls a method isDirty() on this domain object, which checks, if data has changed. Then mapper can act accordingly. This also, with some adjustments, can be used for object graphs (if they are not to extensive, in which case you might need to refactor anyway).
Also, if your domain object actually gets mapped to several tables (or even different forms of storage), it might be reasonable to have several checksums, for each set of variables. Since mapper are already written for specific classes of domain object, it would not strengthen the existing coupling.
For PHP you will find some code examples in this ansewer.
Note: if your implementation is using DAOs to isolate domain objects from data mappers, then the logic of checksum based verification, would be moved to the DAO.
Unit of Work
This is the "industry standard" for your problem and there is a whole chapter (11th) dealing with it in PoEAA book.
The basic idea is this, you create an instance, that acts like controller (in classical, not in MVC sense of the word) between you domain objects and data mappers.
Each time you alter or remove a domain object, you inform the Unit of Work about it. Each time you load data in a domain object, you ask Unit of Work to perform that task.
There are two ways to tell Unit of Work about the changes:
caller registration: object that performs the change also informs the Unit of Work
object registration: the changed object (usually from setter) informs the Unit of Work, that it was altered
When all the interaction with domain object has been completed, you call commit() method on the Unit of Work. It then finds the necessary mappers and store stores all the altered domain objects.
Level 3:
At this stage of complexity the only viable implementation is to use Unit of Work. It also would be responsible for initiating and committing the SQL transactions (if you are using SQL database), with the appropriate rollback clauses.
P.S.
Read the "Patterns of Enterprise Application Architecture" book. It's what you desperately need. It also would correct the misconception about MVC and MVC-inspired design patters, that you have acquired by using Rails-like frameworks.
We develop the back office application with quite large Db.
It's not reasonable to load everything from DB to memory so when model's proprties are requested we read from DB (via EF)
But many of our UIs are just simple lists of entities with some (!) properties presented to the user.
For example, we just want to show Id, Title and Name.
And later when user select the item and want to perform some actions the whole object is needed. Now we have list of items stored in memory.
Some properties contain large textst, images or other data.
EF works with entities and reading a bunch of large objects degrades performance notably.
As far as I understand, the problem can be solved by creating lightweight entities and using them in appropriate context.
First.
I'm afraid that each view will make us create new LightweightEntity and we eventually will end with bloated object context.
Second. As the Model wraps EF we need to provide methods for various entities.
Third. ViewModels communicate and pass entities to each other.
So I'm stuck with all these considerations and need good architectural design advice.
Any ideas?
For images an large textst you may consider table splitting, which is commonly used to split a table in a lightweight entity and a "heavy" entity.
But I think what you call lightweight "entities" are data transfer objects (DTO's). These are not supplied by the context (so it won't get bloated) but by projection from entities, which is done in a repository or service.
For projection you can use AutoMapper, especially its newer feature that I describe here. This allows you to reduce the number of methods you need to provide "for various entities" (DTO's), because the type to project to can be given in a generic type parameter.
I'm implementing a new iPhone app and am relatively new to Cocoa development overall. I am at the stage of choosing how the persistence layer of this app will work, and it looks like I'm basically choosing between Core Data and sqlite3.
The persisted models in this app are intended to have a schema that is loaded at runtime (from some kind of defn file, probably XML). By which I mean, this app is intended to have objects that are user-definable to some extent, e.g. the Customer type (which has certain built-in fields like "name" and "email") can be modified to have extra fields based on the user's specific needs (e.g. a user might want to add a "favourite fruit" field to their Customer type).
Having said that, will Core Data work for an app with a non-baked-in data model like this? I've just started playing around with the Core Data object designer thing in XCode and it seems like this thing wants to work with objects that have fixed fields that are compiled in.
I'm definitely trying to take the path of least resistance here, and I can see the benefits of using an Apple-supplied data framework, but don't want to start down that path if it's going to lock me into a data model that's defined at compile time.
The Core Data data model needs to be defined at compile time, but that does not mean you can't allow for custom fields to be added and used by end users.
It just means that you would define an entity for custom fields and create the fields as objects.
It is best to design a data model that meets your needs rather than think of how you would solve the problem in SQL.